Robots are now commonplace in a typical manufacturing environment. Industrial robots are used in many industries for manufacturing products. For example, in the aerospace industry, robots have been employed to work on components such as wing assemblies and fuselages. Robots, provided with various end effectors and tools, are now moving work pieces around the manufacturing environment at considerable speed. As more robots are employed in the same manufacturing environment, the potential for a collision between a robot, or its tool or end-effector, and other objects in the robot's workspace or even other parts of the same robot increases. Any collision can cause considerable damage to the robot and other objects involved in the collision, resulting in extensive undesirable repair costs and down time in any manufacturing process associated with the robot.
When a robot is being programed for a new operation and the robot is first being brought online in a workspace, there are higher risks of collision than when a robot is already in operation. The robot is first programmed offline using computer-aided design (CAD) models of the robot and workspace. The path of a tool center point (TCP) of the robot's tool is programmed so that the robot can conduct a manufacturing operation. However, the simulated CAD model of the workspace may not be exactly the same as the actual workspace. To address this issue, most industrial robotic manipulators offer a manual mode, or “teach” mode, where the operator can control the robot using a teach pendant or similar remote control device. Teach mode operation is often used to “touch-up” or adjust offline-created robot programs to account for variation between simulated CAD models, which are employed by the offline programming software, and the as-built workspace. Teach mode operation is used frequently during commissioning of a new robotic workspace and creates a significantly higher risk of collision between the robot, tooling, work piece, and other components in the workspace because a human operator is directly in control of the robot. In some industries, such as aerospace, the high value of the work piece makes the risk of collision unacceptably high because rework is costly and production schedules are tight.
To prevent damage from collisions, some robot manufacturers offer collision detection methods that monitor current draw on each of the robot's joint axes to detect when each joint actuator is drawing more than a specified amount of current, possibly signifying a collision. However, normal acceleration and deceleration may also cause higher current draw, making this approach not entirely reliable, as the current monitoring sensitivity must typically be hand-tuned by the operator. Another option, offered by robot manufacturers, as shown in FIG. 1, is a zone-based monitoring feature 10 where the user can define simple polygonal keep-in and keep-out regions 20. During operation, a robot controller 30 monitors various elements 40 of a robot 50 as robot 50 moves relative to a work surface 60, both in teach mode and during normal operation, and immediately halts robot 50 when the robot's motion enters keep-out region 20 or leaves a keep-in region (not shown). However, this zone-based approach is limited in what types of environments it can monitor. Within the aerospace industry, large curved components such as wing assemblies or fuselages are common, which implies that simple zone-based approaches are not adequate for robotic collision avoidance during teach mode operation. Also, numerous aircraft have features like inlet ducts, and robotic end-effectors can be used for operations inside these ducts (e.g., coating or de-coating operations). It would be nearly impossible to protect such areas with a zone-based approach because there is a practical limit to the number of zones that can be defined, and each zone is a simple convex polyhedron that does not support complexities like holes (i.e., toruses are not an option). Other sensor-based approaches can involve outfitting a robot with touch sensors, which can be cost prohibitive to protect all parts of the robot. Non-contact sensors, like 3D laser scanners, could be used to scan the robot and its environment but might not always be able to see all parts of the robot due to “shadows,” which occur when a part of the geometry is hidden from the sensor.
There exists a need in the art to prevent robots from colliding with surrounding objects of complex shape during a teach mode.